Road network and GPS tracking with data processing and quality assessment

GPS technology has been embedded into portable, low-cost electronic devices nowadays to track the movements of mobile objects. This implication has greatly impacted the transportation field by creating a novel and rich source of traffic data on the road network. Although the promise offered by GPS devices to overcome problems like underreporting, respondent fatigue, inaccuracies and other human errors in data collection is significant; the technology is still relatively new that it raises many issues for potential users. These issues tend to revolve around the following areas: reliability, data processing and the related application. This thesis aims to study the GPS tracking form the methodological, technical and practical aspects. It first evaluates the reliability of GPS based traffic data based on data from an experiment containing three different traffic modes (car, bike and bus) traveling along the road network. It then outline the general procedure for processing GPS tracking data and discuss related issues that are uncovered by using real-world GPS tracking data of 316 cars. Thirdly, it investigates the influence of road network density in finding optimal location for enhancing travel efficiency and decreasing travel cost. The results show that the geographical positioning is reliable. Velocity is slightly underestimated, whereas altitude measurements are unreliable.Post processing techniques with auxiliary information is found necessary and important when solving the inaccuracy of GPS data. The densities of the road network influence the finding of optimal locations. The influence will stabilize at a certain level and do not deteriorate when the node density is higher.

On processing GPS tracking data of car-movements in Borlänge, Sweden

The advancement of GPS technology enables GPS devices not only to be used as orientation and navigation tools, but also to track travelled routes. GPS tracking data provides essential information for a broad range of urban planning applications such as transportation routing and planning, traffic management and environmental control. This paper describes on processing the data that was collected by tracking the cars of 316 volunteers over a seven-week period. The detailed information is extracted. The processed data is further connected to the underlying road network by means of maps. Geographical maps are applied to check how the car-movements match the road network. The maps capture the complexity of the car-movements in the urban area. The results show that 90% of the trips on the plane match the road network within a tolerance.

Reliability of GPS based traffic data: an experimental evaluation

GPS tracking of mobile objects provides spatial and temporal data for a broad range of applications including traffic management and control, transportation routing and planning. Previous transport research has focused on GPS tracking data as an appealing alternative to travel diaries. Moreover, the GPS based data are gradually becoming a cornerstone for real-time traffic management. Tracking data of vehicles from GPS devices are however susceptible to measurement errors – a neglected issue in transport research. By conducting a randomized experiment, we assess the reliability of GPS based traffic data on geographical position, velocity, and altitude for three types of vehicles; bike, car, and bus. We find the geographical positioning reliable, but with an error greater than postulated by the manufacturer and a non-negligible risk for aberrant positioning. Velocity is slightly underestimated, whereas altitude measurements are unreliable.

Utveckling av metod för att bedöma behovet av ogräsbekämpning i spår

A system for weed management on railway embankments that is both adapted to the environment and efficient in terms of resources requires knowledge and understanding about the growing conditions of vegetation so that methods to control its growth can be adapted accordingly. Automated records could complement present-day manual inspections and over time come to replace these. One challenge is to devise a method that will result in a reasonable breakdown of gathered information that can be managed rationally by affected parties and, at the same time, serve as a basis for decisions with sufficient precision. The project examined two automated methods that may be useful for the Swedish Transport Administration in the future: 1) A machine vision method, which makes use of camera sensors as a way of sensing the environment in the visible and near infrared spectrum; and 2) An N-Sensor method, which transmits light within an area that is reflected by the chlorophyll in the plants. The amount of chlorophyll provides a value that can be correlated with the biomass. The choice of technique depends on how the information is to be used. If the purpose is to form a general picture of the growth of vegetation on railway embankments as a way to plan for maintenance measures, then the N-Sensor technique may be the right choice. If the plan is to form a general picture as well as monitor and survey current and exact vegetation status on the surface over time as a way to fight specific vegetation with the correct means, then the machine vision method is the better of the two. Both techniques involve registering data using GPS positioning. In the future, it will be possible to store this information in databases that are directly accessible to stakeholders online during or in conjunction with measures to deal with the vegetation. The two techniques were compared with manual (visual) estimations as to the levels of vegetation growth. The observers (raters) visual estimation of weed coverage (%) differed statistically from person to person. In terms of estimating the frequency (number) of woody plants (trees and bushes) in the test areas, the observers were generally in agreement. The same person is often consistent in his or her estimation: it is the comparison with the estimations of others that can lead to misleading results. The system for using the information about vegetation growth requires development. The threshold for the amount of weeds that can be tolerated in different track types is an important component in such a system. The classification system must be capable of dealing with the demands placed on it so as to ensure the quality of the track and other pre-conditions such as traffic levels, conditions pertaining to track location, and the characteristics of the vegetation. The project recommends that the Swedish Transport Administration: Discusses how threshold values for the growth of vegetation on railway embankments can be determined Carries out registration of the growth of vegetation over longer and a larger number of railway sections using one or more of the methods studied in the project Introduces a system that effectively matches the information about vegetation to its position Includes information about the growth of vegetation in the records that are currently maintained of the track’s technical quality, and link the data material to other maintenance-related databases Establishes a number of representative surfaces in which weed inventories (by measuring) are regularly conducted, as a means of developing an overview of the long-term development that can serve as a basis for more precise prognoses in terms of vegetation growth Ensures that necessary opportunities for education are put in place